title: The largest human cognitive performance dataset reveals insights into the effects of lifestyle factors and aging.
abstract: Making new breakthroughs in understanding the processes underlying human cognition may depend on the availability of very large datasets that have not historically existed in psychology and neuroscience. Lumosity is a web-based cognitive training platform that has grown to include over 600 million cognitive training task results from over 35 million individuals, comprising the largest existing dataset of human cognitive performance. As part of the Human Cognition Project, Lumosity's collaborative research program to understand the human mind, Lumos Labs researchers and external research collaborators have begun to explore this dataset in order uncover novel insights about the correlates of cognitive performance. This paper presents two preliminary demonstrations of some of the kinds of questions that can be examined with the dataset. The first example focuses on replicating known findings relating lifestyle factors to baseline cognitive performance in a demographically diverse, healthy population at a much larger scale than has previously been available. The second example examines a question that would likely be very difficult to study in laboratory-based and existing online experimental research approaches at a large scale: specifically, how learning ability for different types of cognitive tasks changes with age. We hope that these examples will provoke the imagination of researchers who are interested in collaborating to answer fundamental questions about human cognitive performance.
authors.affiliation: Lumos Labs Inc. San Francisco, CA, USA.
authors.forename: Daniel A
authors.initials: DA
authors.lastname: Sternberg
authors.forename: Kacey
authors.initials: K
authors.lastname: Ballard
authors.forename: Joseph L
authors.initials: JL
authors.lastname: Hardy
authors.forename: Benjamin
authors.initials: B
authors.lastname: Katz
authors.forename: P Murali
authors.initials: PM
authors.lastname: Doraiswamy
authors.forename: Michael
authors.initials: M
authors.lastname: Scanlon
keywords: aging; cognition; cognitive enhancement; fluid intelligence; learning; lifestyle factors